A Hilbert Space Approach to Variance Reduction
MetadataShow full item record
In this chapter we explain variance reduction techniques from the Hilbert space standpoint, in the terminating simulation context. We use projection ideas to explain how variance is reduced, and to link different variance reduction techniques. Our focus is on the methods of control variates, conditional Monte Carlo, weighted Monte Carlo, stratification, and Latin hypercube sampling.
Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289.
Showing items related by title, author, creator and subject.
An analysis of the factors generating the variance between the budgeted and actual operating results of the Naval Aviation Depot at North Island, California Curran, Thomas; Schimpff, Joshua J. (Monterey, California: Naval Postgraduate School, 2008., 2008-06);For six of the past eight years, naval aviation depot-level maintenances activities have encountered operating losses that were not anticipated in the Navy Working Capital Fund (NWCF) budgets. These unanticipated losses ...
Oswald, Ronald G. (Monterey, California. Naval Postgraduate School, 1998-06);This study examines the logic behind choosing variances and the design of forums during the planning of deliberations in non-routine work environments using a Sociotechnical System design approach. This study was accomplished ...
Trietsch, Dan (Monterey, California. Naval Postgraduate School, 1992-09); NPS-AS-92-021The Probability a Machined part will be defective increases with the variance of the machined dimensions. Even for parts within tolerance, the quality decreases with the variance. By reducing the variance of these dimensions ...